Self-initiated behavioural change and disease resurgence on activity-driven networks

TL;DR

This paper models how individual behavioral adaptations during a second wave of infections affect disease resurgence on activity-driven networks, highlighting the impact of active minorities and social bubbles.

Contribution

It introduces a model analyzing behavioral change scenarios on activity-driven networks, revealing the effects of active minorities and social bubbles on epidemic resurgence.

Findings

Active minorities can undermine collective efforts to control the epidemic.

Social bubbles with normal activity may be less effective than overall social activity reduction.

Behavioral correlations influence epidemic dynamics and control strategies.

Abstract

We consider a population that experienced a first wave of infections, interrupted by strong, top-down, governmental restrictions and did not develop a significant immunity to prevent a second wave (i.e. resurgence). As restrictions are lifted, individuals adapt their social behaviour to minimize the risk of infection. We consider two scenarios. In the first, individuals reduce their overall social activity towards the rest of the population. In the second scenario, they maintain a normal social activity within a small community of peers (i.e., social bubble) while reducing social interactions with the rest of the population. In both cases, we consider possible correlations between social activity and behaviour change, reflecting for example the social dimension of certain occupations. We model these scenarios considering a Susceptible-Infected-Recovered epidemic model unfolding on activity-driven networks. Extensive analytical and numerical results show that i) a minority of very active individuals not changing behaviour may nullify the efforts of the large majority of the population, and ii) imperfect social bubbles of normal social activity may be less effective than an overall reduction of social interactions.